Ear-wearable device with active noise cancellation system that uses internal and external microphones

The present application is a § 371 National Stage application of PCT/US2021/041222 with an international filing date of Jul. 12, 2021, which claims the benefit of U.S. Provisional Patent Application No. 63/054,443, filed Jul. 21, 2020, both of which are incorporated herein by reference in their entireties.

This application relates generally to ear-level electronic systems and devices, including hearing aids, personal amplification devices, and hearables. In one embodiment, an ear-wearable device includes a reference microphone producing a reference signal in response to external sound outside an ear canal of a user. The device includes an error microphone producing an error signal in response to sound inside of the ear canal. A physical propagation path between the reference microphone and the error microphone defines a primary path. The device includes a receiver that produces amplified sound inside of the ear canal. The amplified sound propagates over a secondary path to combine with direct noise at the ear canal, the combination of which is sensed by the error microphone to produce the error signal.

The ear-wearable device includes a processor coupled to the reference microphone, the error microphone, and the receiver. The processor is operable via instructions to: estimate a noise signal from inside the ear canal from the reference signal by filtering with an equalization filter that is based on an estimate of the secondary path and by filtering with a spectrum shaping filter that is based on an estimate of the primary path; input the estimated noise signal from inside the ear canal and the estimated residual noise signal into a least mean square (LMS) algorithm, the LMS algorithm producing coefficients of an adaptive filter; and apply the adaptive filter to the reference signal to produce an anti-noise signal. The anti-noise signal is reproduced by the receiver to actively cancel noise in the ear canal.

The above summary is not intended to describe each disclosed embodiment or every implementation of the present disclosure. The figures and the detailed description below more particularly exemplify illustrative embodiments.

The figures are not necessarily to scale. Like numbers used in the figures refer to like components. However, it will be understood that the use of a number to refer to a component in a given figure is not intended to limit the component in another figure labeled with the same number.

Embodiments disclosed herein are directed to noise reduction in an ear-worn or ear-level electronic device. Such a device may include cochlear implants and bone conduction devices, without departing from the scope of this disclosure. The devices depicted in the figures are intended to demonstrate the subject matter, but not in a limited, exhaustive, or exclusive sense. Ear-worn electronic devices (also referred to herein as “hearing aids,” “hearing devices,” and “ear-wearable devices”), such as hearables (e.g., wearable earphones, ear monitors, and earbuds), hearing aids, hearing instruments, and hearing assistance devices, typically include an enclosure, such as a housing or shell, within which internal components are disposed.

Typical components of a hearing device can include a processor (e.g., a digital signal processor or DSP), memory circuitry, power management and charging circuitry, one or more communication devices (e.g., one or more radios, a near-field magnetic induction (NFMI) device), one or more antennas, one or more microphones, buttons and/or switches, and a receiver/speaker, for example. Hearing devices can incorporate a long-range communication device, such as a Bluetooth® transceiver or other type of radio frequency (RF) transceiver.

The term hearing device of the present disclosure refers to a wide variety of ear-level electronic devices that can aid a person with impaired hearing. The term hearing device also refers to a wide variety of devices that can produce processed sound for persons with normal hearing. Hearing devices include, but are not limited to, behind-the-ear (BTE), in-the-ear (ITE), in-the-canal (ITC), invisible-in-canal (IIC), receiver-in-canal (RIC), receiver-in-the-ear (RITE) or completely-in-the-canal (CIC) type hearing devices or some combination of the above. Throughout this disclosure, reference is made to a “hearing device” or “ear-wearable device,” which are understood to refer to a system comprising a single left ear device, a single right ear device, or a combination of a left ear device and a right ear device.

Embodiments described below include features that reduce the transmission of ambient noise to a user of a hearing device. Ambient noise exists everywhere in our daily environment, such as in a car, in an airplane cabin, or at places near a road, fan etc. Such noise has a significant amount of low-frequency energy and thus strong penetration capability. When a hearing aid (HA) user is exposed to an environment with such noise, the low-frequency part of the noise can bypass the hearing aids and enter the ear canal directly due to relatively longer wavelength. This results in direct noise in the ear canal that causes discomfort, fatigue, and degraded speech intelligibility.

In, a graph shows simulated acoustic transparency for a hearing aid according to an example embodiment. Each curve corresponds to a different attenuation of ambient sound for various fittings of a hearing aid, from fully occluded to fully open. This illustrates that even with a tight fitting, significant low frequency ambient noise components (e.g., less than 1 kHz) can be directly coupled into the ear canal.

Current HA noise reduction algorithms are designed to reduce noise that goes through the signal path of the HAs. Because these signals originate from a microphone, the noise that propagates directly into the ear canal cannot be corrected for by noise reduction algorithms. In embodiments described below, an active noise cancellation (ANC) system is described that is usable on HA devices. In one embodiment, the ANC system deploys a modified hybrid-structure to cancel the component of the direct ambient noise in the acoustic domain, with emphasis on low frequency ranges (i.e. <1500 Hz). A receiver (e.g., loudspeaker) is placed in the ear canal to generate an anti-phase signal based on the signals of one or both of an error microphone (ear-canal) and a reference microphone (external) in order to fully cancel or significantly reduce noise inside the ear canal already. The HA in these embodiments may include an occluded fitting or vented fitting with vent size 1.8 mm or smaller.

In, a diagram illustrates an example of an ear-wearable deviceaccording to an example embodiment. The ear-wearable deviceincludes an in-ear portionthat fits into the ear canalof a user. The ear-wearable devicemay also include an external portion, e.g., worn over the back of the outer ear. The external portionis electrically and/or acoustically coupled to the internal portion. The in-ear portionmay include a receiver, although in some embodiments the receiver may be in the external portion. Similarly, one or both portions,may include an external microphone, as indicated by respective microphones,.

For purposes of ANC, the devicemay also include an internal microphonethat detects sound inside the ear canal. The internal microphonemay also be referred to as an error microphone, as it can detect differences (errors) between noise detected in the ear canaland anti-nose, which is an artificially generated signal output by the receiver to cancel out the noise within the ear canal. For purposes of the following discussion arrowsandrepresent respective primary and secondary paths that will be represented as physical elements of an ANC implementation. The primary pathis a physical propagation path from the external reference microphone (in this example microphone) to the in-ear error microphone. The secondary pathis the physical propagation path from receiverto the error microphone.

There are challenges in deploying ANC into an HA or similar device due to their relatively limited computing resources. For example, an adaptive filtering implementation on HA devices may have a relatively small number of taps, making it difficult to accurately characterize the primary path impulse responses due to the strong resonance mainly at high frequencies. Another challenge in implementing ANC in a HA is the tendency of an HA to shift positions, e.g., due to loose fit, movement of the wearer, etc. Noise suppression systems have been shown to be vulnerable to the change of noise source direction-of arrival angle or wearing angle of the devices that leads to primary path mismatch due to the non-causality issue. Non-causality generally refers to situations where sound arrives at the in-ear microphonebefore the arrival at the external microphone.

In some embodiments described below, a hybrid ANC system is described that uses spectrum shaping and primary path equalization schemes that overcome these constraints of HA. In, a schematic diagram shows an ANC system according to an example embodiment. A reference signal(x(n)) originates from an external microphone. The referencesignal will include at least free field noise, and the signal may include other components of interest (e.g., speech). The primary pathresults in the free field noise x(n) being observed as direct noise in the ear canal x(n), where it is combined with the output y(n) of receiveras indicated by summation block. The receiver's output y(n) includes anti-noise, which has a phase and amplitude that cancels at least some of the direct noise to produce an error signal(e(n)).

The anti-noise signal is produced by an adaptive filter, e.g., finite impulse response (FIR) filter. The filteris adapted via a least mean squares (LMS) algorithm, in this example a normalized least mean squares (NLMS) algorithm. The NLMS algorithmis selected to operate effectively for noise cancellation in hearing aids, as discussed further below. The inputs to the NLMS algorithm include one or both of the reference signaland the error signal. The reference signalmay be equalized via equalizerand passed through a spectrum shaping (SS) filter. The error signalmay also be processed by an SS filter, which is based on an approximation of the primary path. The output of the variable filteris also shaped via equalizerbefore being reproduced via the receiver.

As noted above, the ANC attenuates the direct noise at ear-canal x(n) by broadcasting from the receiveran anti-noise signal y(n) that has a similar magnitude envelope as x(n) but a phase difference of about 180 degrees with respect to x(n). As such, x(n) and y(n) would cancel each other when they meet and a quiet zone (near the eardrum) can be created. The system shown inmay be considered an adaptive feedforward approach, in that the adaptive filterthat develops the anti-noise signal includes inputs,from both the external microphone (feedforward input) and the error microphone (feedback input).

The signal received by the error microphone is the residual noise signal resulting from the linear superposition of the noise in the ear canal and the anti-noise signal y(n) arriving from the receiver driver. The error microphone signaland a secondary path filtered version x(n) of the residual signalare input into a least mean square (LMS) algorithm, the LMS algorithm producing coefficients of the adaptive filter.

The residual noise e(n) is passed to the ANC through the error microphone directly, along with the signalfrom the reference microphone that is placed externally and is closer to the direct noise. The primary pathis the physical propagation path from the external reference microphone to the in-ear error microphone. The impulse response of the so-called secondary path (SP) includes the receiver, the acoustic summation pointand the in-ear microphone. The reference noise estimate x(n) is fed to drive the adaptive filter W(z)to produce the anti-noise. The spectrum shaping filterincludes weighting coefficients for various frequency ranges to reduce the effect of high-frequency resonances in the primary path.

The filtered-X NLMS (FX-NLMS) algorithm is computationally the simplest among common adaptive algorithms. It aims at minimizing the cost function e(n) using the gradient descent algorithm (see, e.g., Haykin, “Adaptive Filter Theory”). The updating of W(n) at time instant n is achieved by sequentially evaluating Equations 1(a)-1(c) below, where: W(n)=[W(n), W(n), . . . , W(n)]denotes the column vector containing the N coefficients of the adaptive filter W(z) at time instant n x(n)=[x(n), x(n), . . . , x(n)]contains the most recent N output samples of X-filter H(z); u is the step size; P(n) and P(n) are the estimates of the absolute amplitudes of the X-filter output x(n) and the error signal e(n); and β is a small positive number serving as the forgetting factor in computing P(n) and P(n).

An alternative to the FxNLMS algorithm is the RLS algorithm. The RLS algorithm provides faster adaptation of the filter coefficients, but at a higher computational complexity. The algorithm is also more sensitive to impulsive noise sources. Impulsive noise describes a noise process that has a rapid of onset of a very high amplitude signal. To address the issues of computational complexity and impulsive noise sensitivity, an FxRLS-FxLMS hybrid algorithm approach has been proposed. Another way of reducing the sensitivity to impulsive noise is to introduce a tan h non-linearity. This non-linearity is inserted just after the spectrum shaping filtersand.

Evaluation of the hybrid ANC shown inin terms of its noise attenuation ability using recorded noise files indicates that performance depends on the characteristics of the secondary and primary paths. At least three prominent factors have been identified: the SP delay, the dynamic range of the PP magnitude response, and the non-causal components of the PP. The latter refers to the sound components that arrive at the in-ear microphone before the arrival at the external microphone due to certain noise source direction of arrival.

The ANC shown inestimates the direct noise x(n) from the reference microphone using its SP-filtered version x(n). The SP delay limits the performance of the FANCs via reducing the correlation between x(n) and x(n). The SP delay can be compensated if it is a minimum phase impulse response. The gain and group delay of the SP under consideration are shown in the graphs of. The actual SP has zeros outside of the unit circle and as a result, it is a non-minimum phase system, which makes it difficult to fully compensation for the SP delay.

The gain and group delay of the PP in consideration are shown in the graphs of. It can be seen that the PP greatly attenuates the signal beyond 1000 Hz and moreover, the dynamic range of its gain in 5 k-6 k Hz reaches a value of −36 dB. The large dynamic range increases the difficulty for the adaptive filter W(z) to compensate the PP gain loss and is hard to achieve using W(z) that is an FIR filter with a limited tap length. Even if the filter order could be increased to obtain improved PP gain approximation, the increased delay of W(z) in the signal path may in turn degrade the noise attenuation ability.

In order to address these issues, the FX-NLMS and FX-RLS algorithms may be guided to focus on a desired frequency region and make it fit the requirement of adaptive filtering with short filter lengths. Unlike the Frequency-domain Adaptive Filtering (FDAF), the FX-NLMS and the FX-RLS based adaptive filtering have equal control over their operational frequency region. However, in the applications to hearing aids it may be desirable to focus on certain low frequencies instead of the whole band as it effectively rolls off the resonance and reduces the effective length of the PP impulse responses such that it fits the FxNLMS system with limited filter length on hearing aids. The reason that PP is highlighted in this context (instead of SP) is that PP impulse response typically has a longer effective length as the external microphone and in-ear mic are more physically separated and the primary path involves the effects of human ear pinna.

In, a block diagram shows the ANC system ofwith additional system components according to an example embodiment. Boxes,represent analog and acoustic components, and boxrepresent digital operations. The free field noise Xt is received by a reference microphone, the output of which is conditioned (e.g., amplified) by an analog front end (AFE). The output of the AFEis converted to digital via an analog-to-digital converter (SDC). The digitized signal is processed by a decimation filterand downsampler. The output (x) of the downsamplerserves as both the feedforward input to ANC as well as the source signal that is adjusted via filterto produce the anti-noise. As seen in block, which includes in-ear acoustic/analog components, an error microphonereceives the combinationof the primary path noisewith the output of the receiver. Similar to the reference microphone, the output of the error microphoneis processed via AFE, ADC, decimation filterand downsampler. Also seen inis an upsampler(which would include interpolation filter) and digital-to-analog converter (DAC).

In, the system ofis shown with additional components of a hearing device according to an example embodiment. Blockprocesses streaming audio data of interest, e.g., speech, music, etc. This streaming audio may originate from the reference microphoneor another audio transducer (not shown). The processing by blockmay include analog processing, ADC, etc. A compensation processing blockperforms specific processing of the audio signal to compensate for hearing loss, such as speech recognition/enhancement, noise reduction, etc. The resulting hearing-loss-compensated audio signal is combined with the anti-noise at block.

In order to provide a feedback signal usable by the adaptive filter, the secondary path will be approximated so as to properly transform the signal received from the error microphone. In one embodiment, a test/calibration operation can involve sending a broadband digital stimulus from the device processor (e.g., based on a signal stored in memory) to the receiver. After the stimulus goes through the rest of the secondary path (e.g., acoustic coupling in the ear canal, error microphoneand its associated processing path), the response is stored by the processor on its memory. Due to the memory size constraints on the hearing device, the stimulus may be chosen as a periodic signal. For example, a complex tone may be used that includes a plurality of pure tones at frequencies of interest.

In one embodiment, the stimulus signal is formed with a sampling frequency of 80 kHz and includes tones of multiples of 100 Hz. The magnitudes of these tones have more emphasis on low frequencies to improve the poor signal-to-noise ratio (SNR) at low frequencies. The complex response of the secondary path is obtained taking the transfer function between the stimulus and the response stored on the hearing device memory. Averaging in the time domain can be used utilized to further increase the SNR.

The ANC system uses a secondary path equalization filter EQ 314 based on an estimate of the secondary path. E(z) is placed in the signal path while the other identical one is placed in the side branch that adjusts the coefficients of W(z). Note that the EQ 314 includes characteristics of the equalizer E(z), the receiver, the acoustic summation pointand the error microphone. This is also the underlying reason behind including equalization filter in the side branch to match the newly obtained SP with an equalizer.

In one embodiment, the SP equalizer includes three parts: a minimum-phase inversion of the SP; a 1st-order low-pass frequency with corner frequency 5 kHz; and second-order high-pass filter (12 db per octave band) with corner frequency dependent on the SP leakage (e.g., the magnitude difference of SP gain between 100 Hz and 1000 Hz). In Listing 1 below, a code listing how the high-pass filter corner frequency (HPFilt_eq_fc) in Hz can be chosen based on secondary path leakage (SPLeakage) in dB according to one example.

After obtaining an infinite impulse response (IIR) filter approximation of the SP, the SP is decomposed into two parts: a minimum-phase part, SP; and an all-pass part, SP. The minimum-phase part is invertible and its group delay can be fully compensated. The all-pass part is non-invertible thus preventing full compensation of the SP delay. The idea is to invert the minimum-phase part of the SP and leave the all-pass part intact. An example is given in the graphs of, which show a designed compensation filter and compensated SP according to an example embodiment.

A hybrid control system with practical primary path models can be implemented in a hearing device, assuming that both external microphone and internal microphone are on the same low-delay DSP path. Using prototypes that deploy both external and in-ear microphones on in-the-canal (ITC) hearing aid shells, the primary path measurement was conducted using an overhead headset in order to alleviate the non-causal issue. An over-the ear, open-back set of headphones was put over the head with the hearing device inserted for the measurements of related transfer function responses. The response of the headphones were pre-equalized for a flat magnitude response at the eardrum and the complex tone stimulus noise level was pre-calibrated to be at 80 dB sound pressure level (SPL) at ear position. The goal was to define the derived primary path responses using inverse filter approach reduces the residual error e(n) as defined as in Equation (2) below.()=()−()*()  (2)

The length of the primary path filter used was, which is the maximum length available in the device firmware. It is also worthy to note that the length of the filters also affects the minimization of the residual error. Generally, the longer the filter length is, the smaller the error would be. The motivation for deploying this PP path measurement approach is to attenuate the non-causal components that lead to relatively large residual error in Equation (2). A reason for this residual error is that sound arriving at the inner microphone before arrives at the outer microphone for some noise fields including a diffuse noise field, which is a sign of non-causality. Impulse response and spectrum of this approach is shown in the graphs of.

The broad-band residual error as seen inremains relatively large due to the fact the non-causality could not be fully eluded. It should be noted that these residual errors are based on broadband. It is shown inthat the residual error at low and mid frequency ranges (e.g., the frequency range of ANC interest) is limited and the non-causal design mostly improves the performance of residual errors at high frequencies (i.e. >5 khz). This insight can be useful as the proposed spectrum shaping scheme assigns low importance to the adaptive filtering over the frequency ranges that features high dynamic resonances. Therefore, the impact of residual error over those frequency ranges can be rolled off. Given the derived responses of the primary paths based on the complex-tone measurements, a cascaded biquad transfer function can be used to conduct the IIR filter approximation using the similar SP approximation approach described above.

High-order IIR filters can be highly sensitive to quantization of filter coefficients and can easily become unstable. The instability issue is much alleviated with first and second-order filters. Higher-order filters are typically implemented as serially cascaded biquad filters. A biquad filter is a second order recursive linear filter, containing two poles and two zeros. The two poles of the biquad filter must be inside the unit circle for it to be stable.

Primary path equalization was also shown in embodiments described above. The goal of the primary path equalization is to eliminate the minimum phase part and make the group delay flat over the frequency range of interests to compensate for characteristics of the primary path. It also equalizes the dynamic range of the PP IIR filter using 1st order high-pass and low-pass filters, which effectively reduces the effective length of the impulse responses such that it fits the adaptive filtering with limited filter length. Given the characteristics of the PP responses, the cut-off frequency of the 1st order high-pass and low-pass filters may be set at around 50 Hz and 2-2.5 kHz respectively for the spectrum shaping filter. The PP equalizer may also include a minimum-phase inversion of the PP together with the high- and low-pass filters.

By looking into a set of formulated reference PP paths with simpler responses, e.g. lower order BR filters, it suggests that the main limiting factor for the hybrid system with practical PPs is due to the limited taps number of FIR filter in the adaptation. The wide dynamic range of the measured PPs (especially the major resonance from 6 kHz to 7 kHz) make the effective lengths for the PP impulse responses significantly longer than the normal secondary paths (or equalized secondary paths). The term “effective length N” is defined as the tap N where h(1:N) includes 98% of the energy of the impulse response h. Due to the increased spacing between microphones, the primary path is longer than the secondary path The number of taps for the FIR filter for FxNLMS adaptation may be confined to 40 due to firmware capabilities, which is insufficient to characterize the full properties of the PPs, as shown in the graphs of.

One design goal is reduces the effective length of the impulse responses such that it fits a FxNLMS system with limited filter length. However, unlike the secondary path, the primary paths are physical paths between two microphones, so the path cannot be altered by the addition of a filter, which makes it difficult to add an equalization module that equalizes the dynamic range of the PP IIR filter. One solution is to devise a spectrum shaping filter that controls the importance of adaptive filtering on different frequency ranges so that it has nulls at the primary path resonance frequencies, as well as at very low frequency ranges where the measurement is inaccurate (i.e. <50 Hz). The equalized PP (as described previous section) is used as the spectrum shaping filter. Examples of the spectrum shaping filter calculated based on real subject PP measurements are given in.

In, a block diagram illustrates hardware of an ear-worn electronic devicein accordance with any of the embodiments disclosed herein. The deviceincludes a housingconfigured to be worn in, on, or about an ear of a wearer. The deviceshown incan represent a single hearing device configured for monaural or single-ear operation or one of a pair of hearing devices configured for binaural or dual-ear operation. The deviceshown inincludes a housingwithin or on which various components are situated or supported. The housingcan be configured for deployment on a wearer's ear (e.g., a behind-the-ear device housing), within an ear canal of the wearer's ear (e.g., an in-the-ear, in-the-canal, invisible-in-canal, or completely-in-the-canal device housing) or both on and in a wearer's ear (e.g., a receiver-in-canal or receiver-in-the-ear device housing).

The hearing deviceincludes a processoroperatively coupled to a main memoryand a non-volatile memory. The processorcan be implemented as one or more of a multi-core processor, a digital signal processor (DSP), a microprocessor, a programmable controller, a general-purpose computer, a special-purpose computer, a hardware controller, a software controller, a combined hardware and software device, such as a programmable logic controller, and a programmable logic device (e.g., FPGA, ASIC). The processorcan include or be operatively coupled to main memory, such as RAM (e.g., DRAM, SRAM). The processorcan include or be operatively coupled to non-volatile (persistent) memory, such as ROM, EPROM, EEPROM or flash memory. As will be described in detail hereinbelow, the non-volatile memoryis configured to store instructions that facilitate using a DNN based sound enhancer.

The hearing deviceincludes an audio processing facility operably coupled to, or incorporating, the processor. The audio processing facility includes audio signal processing circuitry (e.g., analog front-end, analog-to-digital converter, digital-to-analog converter, DSP, and various analog and digital filters), a microphone arrangement, and a speaker or receiver. The microphone arrangementcan include one or more discrete microphones or a microphone array(s) (e.g., configured for microphone array beamforming). Each of the microphones of the microphone arrangementcan be situated at different locations of the housing. It is understood that the term microphone used herein can refer to a single microphone or multiple microphones unless specified otherwise.

At least one of the microphonesis a reference microphone producing a reference signal in response to external sound outside an ear canal of a user. Another of the microphonesis an error microphone producing an error signal in response to sound inside of the ear canal. A physical propagation path between the reference microphone and the error microphone defines a primary path of the hearing device. The speaker/receiverproduces amplified sound inside of the ear canal. The amplified sound propagates over a secondary path to combine with direct noise at the ear canal, the summation of which is sensed by the error microphone to produce the error signal.

The hearing devicemay also include a user interface with a user control interfaceoperatively coupled to the processor. The user control interfaceis configured to receive an input from the wearer of the hearing device. The input from the wearer can be any type of user input, such as a touch input, a gesture input, or a voice input. The user control interfacemay be configured to receive an input from the wearer of the hearing devicesuch as shown in.

The hearing devicealso includes an active noise cancellation moduleoperably coupled to the processor. The active noise cancellation modulecan be implemented in software, hardware, or a combination of hardware and software. The active noise cancellation modulecan be a component of, or integral to, the processoror another processor coupled to the processor. The active noise cancellation moduleis operable to estimate a noise signal from inside the ear canal from the reference signal based on an estimate of the primary path. A residual noise signal is estimated from the error signal based on an estimate of the secondary path. The estimated noise signal from inside the ear canal and the estimated residual noise signal are input into a least mean square (LMS) algorithm that produces coefficients of an adaptive filter which is applied to the reference signal to produce an anti-noise signal. The anti-noise signal is reproduced by the receiverto actively cancel noise in the ear canal

The hearing devicecan include one or more communication devicescoupled to one or more antenna arrangements. For example, the one or more communication devicescan include one or more radios that conform to an IEEE 802.11 (e.g., WiFi®) or Bluetooth® (e.g., BLE, Bluetooth® 4. 2, 5.0, 5.1, 5.2 or later) specification, for example. In addition, or alternatively, the hearing devicecan include a near-field magnetic induction (NFMI) sensor (e.g., an NFMI transceiver coupled to a magnetic antenna) for effecting short-range communications (e.g., ear-to-ear communications, ear-to-kiosk communications).

The hearing devicealso includes a power source, which can be a conventional battery, a rechargeable battery (e.g., a lithium-ion battery), or a power source comprising a supercapacitor. In the embodiment shown in, the hearing deviceincludes a rechargeable power sourcewhich is operably coupled to power management circuitry for supplying power to various components of the hearing device. The rechargeable power sourceis coupled to charging circuitry. The charging circuitryis electrically coupled to charging contacts on the housingwhich are configured to electrically couple to corresponding charging contacts of a charging unit when the hearing deviceis placed in the charging unit.

In, a flowchart shows a method according to example embodiment. Generally, the method can be implemented within an infinite loop in a hearing device. As shown in, a method involves receivinga reference signal from a reference microphone in response to external sound outside an ear canal of a user. An error signal is receivedfrom an error microphone in response to sound inside of the ear canal. A physical propagation path between the reference microphone and the error microphone defines a primary path. Amplified sound produced inside of the ear canal by a receiver propagates over a secondary path to combine with direct noise at the ear canal, the summation of which is sensed by the error microphone to produce the error signal;